# -----------------------------------------------------------------------------
# This file was autogenerated by symforce from template:
# ops/CLASS/lie_group_ops.py.jinja
# Do NOT modify by hand.
# -----------------------------------------------------------------------------
# ruff: noqa: PLR0915, F401, PLW0211, PLR0914
import math
import typing as T
import numpy
import sym
[docs]class LieGroupOps(object):
"""
Python LieGroupOps implementation for :py:class:`symforce.cam.polynomial_camera_cal.PolynomialCameraCal`.
"""
[docs] @staticmethod
def from_tangent(vec, epsilon):
# type: (numpy.ndarray, float) -> sym.PolynomialCameraCal
# Total ops: 0
# Input arrays
if vec.shape == (8,):
vec = vec.reshape((8, 1))
elif vec.shape != (8, 1):
raise IndexError(
"vec is expected to have shape (8, 1) or (8,); instead had shape {}".format(
vec.shape
)
)
# Intermediate terms (0)
# Output terms
_res = [0.0] * 8
_res[0] = vec[0, 0]
_res[1] = vec[1, 0]
_res[2] = vec[2, 0]
_res[3] = vec[3, 0]
_res[4] = vec[4, 0]
_res[5] = vec[5, 0]
_res[6] = vec[6, 0]
_res[7] = vec[7, 0]
return sym.PolynomialCameraCal.from_storage(_res)
[docs] @staticmethod
def to_tangent(a, epsilon):
# type: (sym.PolynomialCameraCal, float) -> numpy.ndarray
# Total ops: 0
# Input arrays
_a = a.data
# Intermediate terms (0)
# Output terms
_res = numpy.zeros(8)
_res[0] = _a[0]
_res[1] = _a[1]
_res[2] = _a[2]
_res[3] = _a[3]
_res[4] = _a[4]
_res[5] = _a[5]
_res[6] = _a[6]
_res[7] = _a[7]
return _res
[docs] @staticmethod
def retract(a, vec, epsilon):
# type: (sym.PolynomialCameraCal, numpy.ndarray, float) -> sym.PolynomialCameraCal
# Total ops: 8
# Input arrays
_a = a.data
if vec.shape == (8,):
vec = vec.reshape((8, 1))
elif vec.shape != (8, 1):
raise IndexError(
"vec is expected to have shape (8, 1) or (8,); instead had shape {}".format(
vec.shape
)
)
# Intermediate terms (0)
# Output terms
_res = [0.0] * 8
_res[0] = _a[0] + vec[0, 0]
_res[1] = _a[1] + vec[1, 0]
_res[2] = _a[2] + vec[2, 0]
_res[3] = _a[3] + vec[3, 0]
_res[4] = _a[4] + vec[4, 0]
_res[5] = _a[5] + vec[5, 0]
_res[6] = _a[6] + vec[6, 0]
_res[7] = _a[7] + vec[7, 0]
return sym.PolynomialCameraCal.from_storage(_res)
[docs] @staticmethod
def local_coordinates(a, b, epsilon):
# type: (sym.PolynomialCameraCal, sym.PolynomialCameraCal, float) -> numpy.ndarray
# Total ops: 8
# Input arrays
_a = a.data
_b = b.data
# Intermediate terms (0)
# Output terms
_res = numpy.zeros(8)
_res[0] = -_a[0] + _b[0]
_res[1] = -_a[1] + _b[1]
_res[2] = -_a[2] + _b[2]
_res[3] = -_a[3] + _b[3]
_res[4] = -_a[4] + _b[4]
_res[5] = -_a[5] + _b[5]
_res[6] = -_a[6] + _b[6]
_res[7] = -_a[7] + _b[7]
return _res
[docs] @staticmethod
def interpolate(a, b, alpha, epsilon):
# type: (sym.PolynomialCameraCal, sym.PolynomialCameraCal, float, float) -> sym.PolynomialCameraCal
# Total ops: 24
# Input arrays
_a = a.data
_b = b.data
# Intermediate terms (0)
# Output terms
_res = [0.0] * 8
_res[0] = _a[0] + alpha * (-_a[0] + _b[0])
_res[1] = _a[1] + alpha * (-_a[1] + _b[1])
_res[2] = _a[2] + alpha * (-_a[2] + _b[2])
_res[3] = _a[3] + alpha * (-_a[3] + _b[3])
_res[4] = _a[4] + alpha * (-_a[4] + _b[4])
_res[5] = _a[5] + alpha * (-_a[5] + _b[5])
_res[6] = _a[6] + alpha * (-_a[6] + _b[6])
_res[7] = _a[7] + alpha * (-_a[7] + _b[7])
return sym.PolynomialCameraCal.from_storage(_res)